code: def _xzx_decomposition(U, wire, return_global_phase=False):
      r"""Computes the decomposition of a single-qubit matrix :math:`U` in terms
      of elementary operations, as a product of Z and X rotations in the form
      :math:`e^{i\gamma} RX(\phi) RZ(\theta) RX(\lambda)`. (batched operation)
  
      Args:
          U (tensor): A :math:`2 \times 2` unitary matrix.
          wire (Union[Wires, Sequence[int] or int]): The wire on which to apply the operation.
          return_global_phase (bool): Whether to return the global phase ``qml.GlobalPhase(-gamma)``
              as the last element of the returned list of operations.
  
      Returns:
          list[Operation]: Returns a list of gates, an ``RX``, an ``RZ`` and
          another ``RX`` gate, which when applied in the order of appearance in the list is
          equivalent to the unitary :math:`U` up to a global phase. If `return_global_phase=True`,
          the global phase is returned as the last element of the list.
  
      **Example**
  
      >>> U = np.array([
      ...     [-0.28829348-0.78829734j, 0.30364367+0.45085995j],
      ...     [ 0.53396245-0.10177564j, 0.76279558-0.35024096j]
      ... ])
      >>> decompositions = _xzx_decomposition(U, 0, return_global_phase=True)
      >>> decompositions
      [RX(12.416147693665032, wires=[0]),
       RZ(1.3974974090935608, wires=[0]),
       RX(11.448040119199066, wires=[0]),
       GlobalPhase(1.1759220332464762, wires=[])]
  
      """
  
      # Small number to add to denominators to avoid division by zero
      EPS = 1e-64
  
      # Choose gamma such that exp(-i*gamma)*U is special unitary (detU==1).
      U = math.expand_dims(U, axis=0) if len(U.shape) == 2 else U
      U_det1, gammas = _convert_to_su2(U, return_global_phase=True)
  
      # Compute \phi, \theta and \lambda after analytically solving for them from
      # U_det1 = RX(\phi) RZ(\theta) RX(\lambda)
      sum_diagonal_real = math.real(U_det1[:, 0, 0] + U_det1[:, 1, 1])
      sum_off_diagonal_imag = math.imag(
          U_det1[:, 0, 1] + U_det1[:, 1, 0]
      )
      phi_plus_lambdas_d2 = math.arctan2(
          -sum_off_diagonal_imag, sum_diagonal_real + EPS
      )
      diff_diagonal_imag = math.imag(U_det1[:, 0, 0] - U_det1[:, 1, 1])
      diff_off_diagonal_real = math.real(
          U_det1[:, 0, 1] - U_det1[:, 1, 0]
      )
      phi_minus_lambdas_d2 = math.arctan2(
          diff_off_diagonal_real, -diff_diagonal_imag + EPS
      )
      lams = phi_plus_lambdas_d2 - phi_minus_lambdas_d2
      phis = phi_plus_lambdas_d2 + phi_minus_lambdas_d2
  
      # Compute \theta
      thetas = math.where(
          math.isclose(
              math.sin(phi_plus_lambdas_d2),
              math.zeros_like(phi_plus_lambdas_d2),
          ),
          2
          * math.arccos(
              sum_diagonal_real
              / (2 * math.cos(phi_plus_lambdas_d2) + EPS)
          ),
          2
          * math.arccos(
              -sum_off_diagonal_imag
              / (2 * math.sin(phi_plus_lambdas_d2) + EPS)
          ),
      )
  
      phis, thetas, lams, gammas = map(
          math.squeeze, [phis, thetas, lams, gammas]
      )
  
      phis = phis % (4 * np.pi)
      thetas = thetas % (4 * np.pi)
      lams = lams % (4 * np.pi)
  
      operations = [
          qml.RX(lams, wire),
          qml.RZ(thetas, wire),
          qml.RX(phis, wire),
      ]
      if return_global_phase:
          operations.append(qml.GlobalPhase(-gammas))
  
      return operations
  
file_path: pennylane/pennylane/ops/op_math/decompositions/single_qubit_unitary.py
imports: import numpy
  import pennylane
  from pennylane import math
label_desc: Use image node_id 6 for calling a global function with example usage: _xzx_decomposition(U, wire, return_global_phase) and returns: operations